جست‌وجوی استاد و پژوهشگر

• Teacher Education
• Literacy Instruction
• Equitable Education
• +۳ مورد دیگر

MICHELLE KWOK is an Assistant Professor in the Department of TEACHING, LEARNING & CULTURE at Texas A&M University’s School of Education and Human Development. Her research focuses on teacher education, literacy instruction, and equitable pedagogy, with a particular interest in applying linguistics to improve STEM education. She leads projects on math word problem linguistics and preservice teachers’ beliefs about equity. Education: PhD (2016) and MA (2010) in Educational Studies: Literacy, Language, and Culture from the University of Michigan. Research Interests: Equitable literacy practices in content-area teaching Linguistics applications in STEM problem-solving Preservice teacher beliefs and professional development Culturally relevant pedagogy Notable Awards: 2022 Association of Former Students College Level Teaching Excellence Award 2020 Literacy Research Association Best Paper Award $74,680 in grant funding for intercultural education initiatives Leadership: Coordinates the Online MEd Generalist Program and chaired LRA’s Teacher Education division (2019–2022). Teaches courses on literacy assessment, multicultural education foundations, and content-area reading. Grants & Funding: Current $14,680 grant (2023–2025) supports virtual intercultural engagement programs. Prior grants include a $60,000 Presidential Transformational Teaching Grant (2020–2022).

Yang Yangمشاهده پروفایل

استادیار

• Data Mining
• Machine Learning
• Computational Social Science
• +۴ مورد دیگر

Yang Yang is an Assistant Professor at the Mendoza College of Business, University of Notre Dame. He holds a PhD in Computer Science from the same institution and previously served as Assistant Professor at Syracuse University and Research Assistant Professor at Northwestern Institute on Complex Systems (NICO) and Kellogg School of Management. His research focuses on data mining, machine learning, computational social science, and science of science, particularly exploring how social networks influence leadership attainment and innovation dynamics in scientific contexts. Yang's work bridges computer science and social sciences, examining topics like team composition effects on innovation, media's role in science communication, and gender disparities in leadership. His research has been published in top-tier venues such as PNAS, KDD, ICDM, and featured in media outlets like Forbes, The Washington Post, and WIRED. His recent technical contributions include advancements in multimodal AI, remote sensing interpretation, and video synthesis techniques. Notable projects include geo-localization systems using satellite imagery, transformative video generation models, and human-centric animation technologies leveraging diffusion models and transformers.

Xin Weiمشاهده پروفایل

استاد مهمان

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Xin Wei is a Visiting Professor in the Physics Department at Stanford University, affiliated with the School of Humanities and Sciences. Their research focuses on advancing artificial intelligence, machine learning, and natural language processing, with a particular emphasis on multimodal models, data valuation, and ethical AI practices. Xin Wei’s work bridges theoretical contributions with applied studies in areas such as large language models, peer review systems, and clinical AI adoption. They have published extensively on topics including model card analysis, distribution shifts, and dataset documentation. Research interests include the societal impact of AI, improving model transparency, and addressing disparities in AI performance across diverse datasets. Their recent work explores methods to enhance multimodal state-space models, adaptive agentic systems, and the ethical implications of AI in scientific writing and healthcare. Key contributions include frameworks like LlamaFusion for multimodal generation, Metashift for evaluating distribution shifts, and Opendataval for data valuation benchmarking. Xin Wei’s interdisciplinary approach integrates computer science, physics, and ethics to drive innovation while ensuring responsible AI development.

Ahmed Farooqمشاهده پروفایل

مدرس

• Haptics
• Multimodal Interaction
• Human-Computer Interaction
• +۷ مورد دیگر

Ahmed Farooq is a University Lecturer and Senior Researcher at the Tampere Unit for Computer-Human Interaction (TAUCHI), Tampere University. He holds a PhD in Computer Science and has over 20 years of experience in haptic and multimodal interaction systems. His current role combines academic teaching (e.g., HI 520 Haptic Interaction course) with advanced research in haptic mediation, wearable technologies, and AI-driven interaction systems. Affiliations: TAUCHI Research Group, Tampere Institute of Advanced Studies (TIAS) Positions: Permanent Lecturer (2024–present), TIAS Postdoctoral Fellow (2022–2024), Visiting Researcher at McGill University (2020) and Purdue University (2019–2020) Research Interests: Haptic signal mediation, 3D-printed haptic waveguides, magnetorheological fluid actuators, AI integration in multimodal systems (e.g., TAUCHI-GPT), and applications in automotive UI, VR/XR, and food interaction systems. His work focuses on reducing driver distraction, enhancing tactile feedback in virtual environments, and developing ethical AI tools. Key Projects: Origo Steering Wheel (German Design Award, 2021), Augmented Eating Experiences (AEE), Huawei Haptic Mediation, and TAUCHI-GPT open-source AI framework. These projects involve collaboration with industry partners like Huawei and Bentley University. Publications: Over 60 peer-reviewed articles in top venues (ACM, IEEE, EuroHaptics) focusing on haptic actuation, multimodal interaction, and AI ethics. Recent work explores prompt injection attacks in LLMs and implantable haptic actuators. Awards: TIAS Postdoctoral Fellowship (2022–2024), Finnish Cultural Foundation Mobility Grant (2018). His research has led to 9 patents (e.g., multifunctional haptic actuator, 2024) and 6 granted US/Japan patents.

Gunar Schirnerمشاهده پروفایل

دانشیار

• Embedded Systems
• Cyber-Physical Systems
• Hardware/Software Co-Design
• +۴ مورد دیگر

Gunar Schirner is an Associate Professor of Electrical and Computer Engineering at Northeastern University's College of Engineering . He holds a Ph.D. and M.S. from the University of California, Irvine, and a B.Sc. from Berufsakademie Berlin. His research focuses on embedded systems, cyber-physical systems, and hardware/software co-design, with emphasis on embedded vision and system-level methodologies. Education: Ph.D. & M.S. in Electrical and Computer Engineering, University of California, Irvine (2008, 2005) Bachelor's in Computer Engineering, Berufsakademie Berlin, Germany (1998) Research Interests: Embedded system modeling, real-time AI on edge devices, accelerator-rich computing architectures, and assistive robotics. His work bridges algorithm design with system-level implementation, including projects on neural-controlled prosthetics and marine mammal monitoring via passive acoustic sensing. Grants & Collaborations: Schirner leads/navigate grants totaling over $2M from the National Science Foundation (NSF), U.S. Army, and Office of Naval Research, including a $13M Army contract for distributed sensing research. He co-directs the Embedded Systems Laboratory , advancing heterogeneous platform design and embedded vision systems. Students & Impact: His advisees, including Mo Han and Yagmur Gunay, have won best paper awards at PETRA 2019. He actively integrates industry experience (e.g., Alcatel-Lucent) into teaching, mentoring students in both academia and industry.

Elisabeth Andréمشاهده پروفایل

استاد

• Tangible user interfaces
• Perceptive user interfaces
• Interactive multimodal user interfaces
• +۱۰ مورد دیگر

Elisabeth André is a Full Professor of Computer Science and Chair of Multimedia Concepts and Applications at University of Augsburg, where she has been faculty since 2001. She previously served as Managing Director of the Institute for Computer Science at Augsburg University from 2004 to 2006. Professor André has received multiple prestigious professorship offers, including W3-Professorships in Human-Computer Interaction and Cognitive Systems from University of Stuttgart and Human-Machine Interaction from Otto-Friedrich-Universität Bamberg in 2009. Her academic journey began with a Diploma in Computer Science (1988) and Dr. rer. Nat. (1995) from Saarland University. Before joining Augsburg, she spent over a decade as a Scientific Researcher at DFKI GmbH (German Research Center for Artificial Intelligence), where she rose to Principal Researcher and was appointed a DFKI Research Fellow. Professor André's research focuses on designing and evaluating interactive multimodal user interfaces, experimental learning environments with animated characters, and affective computing. She is internationally recognized as a pioneer in embodied conversational agents, having organized one of the first international workshops on the topic in 1997. Her work stands out for its empirical foundation, including extensive corpus studies of human behaviors to inform virtual agent behavior modeling. Notably, she has conducted significant cross-cultural research with Japanese partners to develop culture-specific behaviors in virtual agents. Her publication record shows a consistent trajectory of innovation in human-computer interaction, with particular emphasis on multimodal analysis, gaze behavior simulation, and emotion recognition systems. The research trends in her recent work demonstrate increasing sophistication in input recognition methods and the development of practical toolboxes (AuBT, EmoVoice, SSI) that have been adopted by research institutions worldwide. 2007 Alcatel-Lucent Fellowship at Universität Stuttgart Best Paper Finalist at International Conference on Intelligent Virtual Agents (2007-2009) 2005 Convivio Best Demo Award 2000 Best Paper Award at International Conference on Intelligent User Interfaces 1998 RoboCup Scientific Award Multiple student projects winning international awards including GALA Awards and TEI conference awards Professor André has supervised 2 completed dissertations and is currently guiding 11 PhD students and 1 Habilitation candidate. Her leadership extends to major research projects including EU-funded initiatives (METABO, E-Circus, IRIS, DynaLearn, CALLAS) and DFG projects (CUBE-G, OC-Trust). She serves on numerous editorial boards and has held significant organizational roles in major conferences including IUI, IVA, and CASA. Her laboratory has developed multiple software toolkits that are used internationally in large-scale research projects, demonstrating the practical impact of her work. Current research directions include advanced emotion recognition systems, culture-adaptive virtual agents, and applications of her technology to educational and healthcare domains.

V. Ashley Villarمشاهده پروفایل

استادیار

• Stellar Astrophysics
• Machine Learning in Astronomy
• Supernova Studies
• +۳ مورد دیگر

Dr. V. Ashley Villar is an Assistant Professor of Astronomy at Harvard University, specializing in using machine learning and data-driven methods to study stellar explosions, mergers, and transient phenomena. She holds a PhD in Astronomy & Astrophysics from Harvard (2020) and a BS in Physics from MIT (2014). Her research focuses on supernova light curves, circumstellar interactions, and binary progenitor systems. She previously held positions at Columbia University as a Simons Junior Fellow and at Penn State as the inaugural Mercedes Richards Career Development Professor. Her work leverages large-scale surveys like LSST and JWST to analyze transients, develop classification tools (e.g., SPLASH, Superphot+), and model explosion mechanisms. Awards include NSF and Ford Foundation fellowships. She collaborates on projects such as the Young Supernova Experiment (YSE) and contributes to multimessenger astronomy efforts linking gravitational waves to electromagnetic counterparts. Key Projects: YSE Data Release 1 (1,975 supernova classifications), extrabol bolometric light curve estimator, SBI++ inference framework Grants: NSF, Simons Foundation, LIGO collaborations Labs/Teams: Harvard CfA Transient Research Group, LIGO HET Response Collaboration Her recent work includes analyzing GRB 221009A's supernova emission, kilonova light-curve interpolation, and binary merger signatures in double-peaked supernovae. She actively develops machine learning tools for transient classification and anomaly detection in big astronomical datasets.

Makeba Parramore Wilbournمشاهده پروفایل

دانشیار

• Developmental Psychology
• Language Acquisition
• Cognitive Development
• +۴ مورد دیگر

Makeba Parramore Wilbourn is an Associate Professor of the Practice in Psychology and Neuroscience at Duke University, affiliated with Trinity College of Arts & Sciences. She holds additional affiliations with the Center for Biobehavioral Health Disparities Research and the Sanford School of Public Policy's Center for Child and Family Policy. Education: Ph.D., Cornell University, 2008 M.A., California State University, Fullerton, 2001 B.A., California State University, Fullerton, 1997 Research Interests: Her work explores how cognition and language interact across development, focusing on the role of gestures, bilingualism, and socio-cultural factors. Key themes include emotion perception in infants, racial biases in emotion reasoning, and the impact of socio-economic status on language development. Grants & Service: Principal Investigator on grants from NSF, RIKEN Brain Science Institute, and others. Service roles include IRB membership, grant review panels, and advocacy for minority faculty. Awards: Notable honors include the Presidential Early Career Award for Scientists and Engineers (PECASE) and NSF CAREER Award. Teaching: Courses span developmental psychology, research methods, and the role of race in development. Wilbourn Infant Lab (WILD): Studies how infants learn language through gestures and cultural contexts, emphasizing equity in early education.

Andreas Møgelmoseمشاهده پروفایل

دانشیار

• Computer Vision
• Artificial Intelligence
• Autonomous Systems
• +۳ مورد دیگر

Andreas Møgelmose is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology under the Technical Faculty of IT and Design. His research focuses on computer vision, artificial intelligence, and their applications in autonomous systems, driver assistance, and industrial vision. He leads projects like AI Color Fashion and Real-world adaption of generative AI for architecture. Møgelmose teaches introductory programming, computer vision, and advanced master's courses, emphasizing practical project-based learning. His work includes developing datasets such as the Multi-view Traffic Intersection Dataset (MTID) and exploring vision-language models for autonomous vehicle safety. He actively engages in media discussions on AI ethics and societal impacts. Research interests span dynamic gesture interpretation for cooperative autonomous vehicles, surgical skill assessment via automated metrics, and multimodal classification of environmental data. He has contributed to over 50 publications, including work on 3D object detection frameworks and generative AI education. Møgelmose collaborates on projects funded by industry partners like COWI and Danish government initiatives. His teaching philosophy centers on blended learning and practical application, fostering innovation in AI and computer vision education. Notable projects include AI:Xpertise Lab (2025–present), which explores AI-driven expertise systems, and collaborations on forest biodiversity analysis using LiDAR and orthophotos. His recent media engagements highlight societal AI challenges, emphasizing responsible implementation in public sectors.

Frank Markمشاهده پروفایل

استاد

• Natural Language Processing
• Computational Research and Modeling
• Social Science
• +۳ مورد دیگر

Frank Mark is a Professor in the Department of Communications at the University at Buffalo (College of Arts and Sciences), with an affiliation to the Institute for Artificial Intelligence and Data Science. He holds a PhD and specializes in computational research, natural language processing, and social science with a focus on nonverbal communication dynamics. His work integrates interdisciplinary methods to study deception detection, facial expression analysis, and multimodal data systems. Research interests prominently include automated facial action coding, intergroup emotions, and the role of nonverbal cues in deception. His publications explore topics like rapport modeling in interviews, evolutionary signals of attraction, and the development of databases like DBATES for analyzing debate speeches' audio, text, and visual features. He has contributed to peer review processes and academic journal governance, emphasizing transparency and data literacy in scholarly communication. Frank Mark's recent work emphasizes technological applications in behavioral analysis, such as laser Doppler vibrometry for facial muscle measurement, and the ethical implications of open data systems. His research bridges computational modeling with psychological insights to address real-world challenges in communication, deception, and social interaction.

• Biological Systems Modeling
• Quantum Optomechanics
• Magnetometry Applications
• +۵ مورد دیگر

Dr. James Bennett is a Post-doctoral Research Fellow in the ARC Centre of Excellence for the Mathematical Analysis of Cellular Systems (MACSYS) at Queensland University of Technology (QUT). He holds a PhD from The University of Queensland (UQ), supervised by Prof. Warwick Bowen, Prof. Halina Rubinsztein-Dunlop (AO, FAA), and Dr. Lars Madsen. His research bridges physics and mathematics, focusing on applying data-driven models to understand complex biological systems. Prior to MACSYS, he specialized in quantum mechanics using optomechanical oscillators and developed magnetic field sensors with applications in navigation and through-earth communication. His academic affiliations include the Faculty of Science and School of Mathematical Sciences at QUT. Bennett teaches Aspects of Computational Science and has prior teaching experience in linear algebra, mechanics, and calculus at Griffith University and UQ. He collaborates with industry partners such as Orica, Defence Science & Technology, and NASA Glenn Research Center on magnetometer technologies for aerospace and mining applications. Education: BSc (Hons I) in Physics, UQ PhD in Physics, UQ Research Interests: Quantum optomechanics Magnetometry for aerospace and environmental applications Mathematical modeling of cellular systems Teaching: Current: Aspects of Computational Science (QUT) Past: Linear Algebra, Mechanics, Calculus (Griffith University) Bennett’s work in MACSYS addresses the interplay between mathematical principles and biological complexity, aiming to uncover foundational biological mechanisms. His publications span optomechanical systems, quantum state manipulation, and sensor technology innovations.

• Geovisualization
• GeoVisual Analytics
• Geoinformation Systems
• +۵ مورد دیگر

Prof. Doris Dransch is a Professor at the Humboldt-Universität zu Berlin's Geographical Institute within the Faculty of Mathematics and Natural Sciences. She holds dual affiliations with the Helmholtz Centre Potsdam GFZ. Her research focuses on geovisualization, geo-analytic systems, and geoinformation management. She has been actively teaching since 1988 at multiple institutions including Humboldt University, TU Berlin, and international universities like Salzburg. PhD: Dr. rer. nat. (Natural Sciences) Her work bridges theoretical cartography with applied geospatial technologies. Key areas include: Dynamic visualization frameworks for geoscientific data Interactive cartographic systems Mobile geoinformation services Multimedia GIS applications Publications span foundational concepts like action-oriented cartography and innovative approaches to spatial data representation. She has authored/co-authored books such as Computer Animation in Cartography (1997) and contributed to major encyclopedic works on geomatics. Professional roles include: National Delegate for Belmont Forum e-Infrastructure (2013–present) Member of German Disaster Management Committee (DKKV) Advisory Board Former Head of DFG's Cartography Commission (1999–2010) Her work emphasizes interdisciplinary applications of geoinformation systems across urban planning, disaster management, and environmental sciences.

Brice Rotureauمشاهده پروفایل

پژوهشگر

• Trypanosomatid parasites
• Neglected Tropical Diseases
• Parasite transmission
• +۷ مورد دیگر

Brice Rotureau is a Director of Research at the Institut Pasteur in Paris and leads the Trypanosome Transmission Group. He also serves as the Director of the Parasitology Unit at the Institut Pasteur of Guinea in Conakry. His research focuses on the development, transmission, diagnostics, and eco-epidemiology of trypanosomatid parasites responsible for neglected tropical diseases such as Human African Trypanosomiasis (sleeping sickness). His research interests include Molecular and cellular biology of Trypanosoma species Parasite transmission mechanisms in tsetse flies Development of CRISPR-based diagnostic tools (e.g., SHERLOCK platform) Epidemiology and zoonotic reservoirs of trypanosomatid diseases Host-pathogen interactions and tissue tropism (skin, adipose) The recent articles highlight a strong trend toward innovative diagnostics (SHERLOCK), metabolic and signaling pathways in parasite development, and the role of alternative reservoirs (skin, adipose tissue) in disease persistence. His work integrates molecular biology, imaging, and field epidemiology to address both fundamental and public health aspects of parasitic diseases. Scientific awards include: Launois Prize, French Academy of Medicine (2023) Deschiens Prize, French Academy of Medicine (2017) Epidaure Prize, Foundation for Medical Research (2008) Annual prize, French Society of Parasitology (2011) Evian-les-Bains Prize, French Academy of Medicine (2009) Brice Rotureau actively advises on research strategy and grant evaluation, serving as an Associate Editor for Microbiol Spectrum and Trop Med Infect Dis , and as a reviewer and evaluator for major funding bodies (ERC, Wellcome Trust, ANR). He mentors students and contributes to teaching parasitology at multiple institutions. His leadership extends to international collaborations, including membership in the SAB of the LAMIVECT consortium and participation in WHO expert panels. He currently coordinates or partners in several ANR and BMGF-funded research projects. He is involved in the HistoPathology Core Facility and Image Analysis Hub at the Institut Pasteur, contributing to the advancement of digital pathology and quantitative histopathology through initiatives like the D-Patho project.

• Cochlear Implants
• Auditory Perception
• Music Perception
• +۳ مورد دیگر

Christina Fuller is a researcher at the University of Groningen, active in interdisciplinary research bridging auditory neuroscience, medical data mining, and cancer therapy analysis. Her work primarily focuses on cochlear implants, music perception, and quality of life assessments for hearing-impaired individuals, while also contributing to symptom analysis in oncology through machine learning techniques. Key Research Areas: Cochlear implants, music perception, human-machine collaboration in clinical contexts, and cancer symptom management. Academic Collaborations: Works with institutions like Advanced Bionics and Mandema Foundation, with international partnerships in data science and oncology. Awards: Recognized with the Mandema Stipendium (2016) for auditory perception research and Advanced Bionics Industry Support (2013) for music therapy development in cochlear implant users. Public Engagement: Frequently contributes to public discourse on hearing rehabilitation through media appearances and community-focused presentations. Dataset Contributions: Created open-access datasets on music perception in implant users, hosted at University of Groningen and DataverseNL.

• Signal Processing
• Machine Learning
• Artificial Intelligence
• +۱۲ مورد دیگر

Arash Mohammadi is an Assistant Professor in the Department of Electrical and Computer Engineering at Concordia University, Montreal, Canada. He holds a PhD from the University of Toronto (2015) and was formerly affiliated with Amirkabir University of Technology, Iran. His research bridges signal processing, artificial intelligence, and biomedical applications. Research Interests: Signal and image processing for healthcare (e.g., lung cancer detection, ECG analysis) Machine learning for smart grids and cyber-physical systems AI in mobile edge computing and 6G networks Transformer and diffusion models for medical and motion data Federated and efficient deep learning for edge devices His recent publications (2021–2025) in top venues like IEEE TSP, ICASSP, and AAAI demonstrate a strong focus on applying cutting-edge AI—especially vision transformers, Mamba architectures, and diffusion models—to critical domains such as medical diagnostics, gesture recognition, and network security. Trends include multimodal fusion, uncertainty quantification, and efficient model design. Scientific Contributions: Developed novel frameworks like NYCTALE and MIXCAPS for lung nodule malignancy prediction Introduced CacheMamba and TEDGE-Caching for edge network optimization Advanced EMG-based gesture recognition using hybrid and transformer models Contributed to cybersecurity in smart grids via attack detection models He actively advises students and collaborates with researchers such as Konstantinos N. Plataniotis and Jamshid Abouei. He has contributed to special issues on neurorehabilitation and AI for COVID-19 diagnosis. His work often involves interdisciplinary teams and real-world applications in healthcare and smart infrastructure.